Coding · Mistral AI

Magistral Chat on SWE-bench Verified: score, rank and what it means

Magistral Chat scores 64.5 on SWE-bench Verified, placing it #222 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
64.5
0–100 scale
Rank
#222
of 600
Percentile
63th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
17.2
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Magistral Chat highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Magistral Chat sits at #222 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 17.2 points. The median model in this index scores 61.0, which puts Magistral Chat above the midpoint.

Mistral AI models average 54.7 on this benchmark. Magistral Chat is 9.8 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among multimodal models, the average is 66.4. Magistral Chat is 1.9 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 64.5 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $4.33 per million input tokens, Magistral Chat is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Grok 3 Mini xAI 200000 $9.67 73.9
Llama 3.1 Cerebras Chat Cerebras 32768 $4.07 76.0
Sonar Reasoning Perplexity 200000 $11.48 76.2
DeepSeek-Coder Chat DeepSeek 200000 $4.20 77.3
Magistral Chat Mistral AI 128000 $4.33 76.8
Llama 3 Hyperbolic Hyperbolic 65536 $3.86 74.5
Nemotron 4 Instruct NVIDIA 65536 $4.10 76.4

Other benchmarks for Magistral Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 77.9 246 59th
GPQA Diamond 72.3 214 64th
HumanEval 81.3 207 66th
MATH-500 83.8 128 79th
AIME 2025 73.7 192 68th
LiveCodeBench 67.5 238 60th
IFEval 83.5 231 62th
TruthfulQA 82.3 124 79th
HellaSwag 86.1 213 65th
MMMU 72.0 246 59th
Arena Elo 1397.1 217 64th

FAQ

What score does Magistral Chat get on SWE-bench Verified?

Magistral Chat scores 64.5 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Magistral Chat rank on SWE-bench Verified?

It ranks #222 of 600 models, in the 63rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is Magistral Chat good at SWE-bench Verified?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the SWE-bench Verified score calculated?

SWE-bench Verified is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Magistral Chat cost?

Magistral Chat costs $4.33 per million input tokens and $16.06 per million output tokens.

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